This disclosure provides a method and system to locate/detect pixels corresponding to static occlusions associated with an image captured scene including a tracked object. According to an exemplary method, pixels corresponding to static occlusions are automatically located by monitoring the motion of single or multiple objects in a scene over time and with the use of an associated accumulator array.
Video-based object tracking is important in computer vision applications, with applications in a wide variety of fields including surveillance and traffic monitoring, video-based vehicle speed estimation, automated parking monitoring, and measuring total experience time in retail spaces.
Static occlusions cause many failures in surveillance applications such as person and vehicle tracking. Knowledge of the locations and appearance of static occluders in a scene can be used by tracking algorithms to reduce object tracking failures. In most tracking algorithms, a track is defined for an object and the object position is updated on a frame-by-frame basis by matching known features and/or blob characteristics of the tracked object as it traverses an area of interest. Object tracking is typically performed by finding the location of the image region showcasing features that best match a current feature representation of the object being tracked. This is usually performed via search/optimization algorithms across regions of interest (ROI) in subsequent frames nearby the location of the object in the current frame. When these features and blobs are occluded by static objects, the object track can be lost since the appearance of the occluded object generally does not match the appearance of the unoccluded object. However, if the tracking algorithm has knowledge of occlusion location and shape within an image of a scene, steps can be taken to mitigate the effect of such obstacles. The present disclosure describes a completely automated method and system for automatically determining the location and appearance of static occlusions in a scene.